VeADK Examples

A hands-on tour of VeADK, from the smallest possible agent to a multi-agent workflow. Each folder is self-contained: a single main.py, an .env.example, and a bilingual README (English + 中文).

中文版见 README.zh.md

Learning path

#	Example	Level	What you'll learn
01	Quickstart	Simple	Agent + Runner, one question
02	Custom tools	Simple	Let the agent call your Python functions
03	Short-term memory	Medium	Multi-turn conversation with a persistent session
04	Web search	Medium	Use a built-in Volcengine tool
05	Knowledgebase RAG	Medium	Ground answers in your own documents
06	Multi-agent workflow	Complex	Compose specialist agents with SequentialAgent
07	Structured output	Medium	Get schema-validated JSON with output_schema
08	Model config	Simple	Model fallbacks + model_extra_config per agent
09	Long-term memory	Complex	Recall facts across sessions (auto_save_session)
10	Agent routing	Complex	A coordinator that delegates to specialists dynamically
11	Tracing	Complex	Observe LLM/tool calls; dump or export spans

There is also a2ui_agent/ — a demo of agent-driven UI, run with veadk frontend --agents-dir examples.

For a deployable full app (web UI + agent API in one container, shipped to Volcengine AgentKit via veadk agentkit), see basic-app/.

The examples are grouped by concept: 01–02 basics, 03 & 09 memory, 04–05 tools & knowledge, 06 & 10 multi-agent, 07–08 model behavior, 11 observability.

Common setup

1. Install VeADK (examples 05 needs the extensions extra):

   pip install veadk-python
   # for the RAG example:
   pip install "veadk-python[extensions]"

2. In each example folder, copy the env template and add your keys:

   cd 01_quickstart
   cp .env.example .env

   VeADK auto-loads .env from the current working directory. You can also use a config.yaml instead — see the configuration docs.

3. Run:

   python main.py

Key concepts in one place

• Agent — model + instruction + tools + memory/knowledge. Created once, reads model config from the environment.
• Runner — drives a conversation; await runner.run(messages=..., session_id=...) returns the final text answer.
• Tools — any Python function with type hints and a docstring; built-ins live under veadk.tools.builtin_tools.
• Memory — short-term (conversation context, keyed by session_id) and long-term (across sessions).
• KnowledgeBase — RAG over your documents; auto-adds a retrieval tool.
• Workflow agents — SequentialAgent, ParallelAgent, LoopAgent to orchestrate multiple agents.

Learn more

• Docs: https://volcengine.github.io/veadk-python/
• Tutorial notebook: veadk_tutorial.ipynb